similar to: regression in batches?

I'm still having difficulties with methods...is the following behavior expected? (This is without loading any libraries) R : Copyright 2003, The R Development Core Team Version 1.7.0 Under development (unstable) (2003-03-31) > ls() character(0) > > diag(2) [,1] [,2] [1,] 1 0 [2,] 0 1 > setGeneric("diag") [1] "diag" > diag(2) Error in

In the last few days I've received couple of messages pointing out that our SparseM package fails to install on the patched version of 1.7.0. Laurent Gaultier kindly suggested that replacing: setGeneric("as.matrix.csr") by setGeneric("as.matrix.csr", function(x, nrow, ncol, eps) standardGeneric("as.matrix.csr")) was sufficient to fix the problem.

Greetings on A.N. Kolmogorov's 100th birthday: I am sure that this is a resolved problem, certainly it has been raised in R help several times before, but I can't seem to find the right clue. I've recently upgraded a G4 to OS 10.2.5 and I thought I would have another go at installing R from source, after failing to accomplish this in 10.1. So with 1.7.0 from CRAN configure seems to

Suppose you have a class, say sex, for lack of a better example, and you are tempted, in defining the behavior of the call, is(x,"sex") to check whether certain basic features are satisfied, not to just trust the claim that x is specified to be of class "sex". `Without delving into details further sanity checking of the structure of the object is sometimes prudent to avoid

Does anyone have any suggestions on perspective plotting of piecewise constant functions? Ideally, I would like something like plot.stepfun for functions that are piecewise constant on polygons. Even pointers to non-R strategies would be welcome at this stage. url: www.econ.uiuc.edu Roger Koenker Dept. of Economics UCL, email rkoenker at uiuc.edu Department of Economics Drayton House, vox:

Dear all, I'm new to matrix operations in R. I couln't find a solution to the following problem among earlier help mails or in An introd to R, I guess because the question is really basic. I want to extract all above the diagonal, i.e. from 1 2 3 4 1 0 26 49 49 2 26 0 44 40 3 49 44 0 21 4 49 40 21 0 I want 26 49 44 49 40 21 Thanks in advance! Sincerely, Tord

Hi, I need to fit a piecewise linear regression. x = c(6.25,6.25,12.50,12.50,18.75,25.00,25.00,25.00,31.25,31.25,37.50,37.50,50.00,50.00,62.50,62.50,75.00,75.00,75.00,100.00,100.00) y = c(0.328,0.395,0.321,0.239,0.282,0.230,0.273,0.347,0.211,0.210,0.259,0.186,0.301,0.270,0.252,0.247,0.277,0.229,0.225,0.168,0.202) there are two change points. so the fitted curve should look like \ \ /\

dear all, I apologize for my delay in replying you. Here my contribution, maybe just for completeness: Similar to "earth", "segmented" also fits piecewise linear relationships with the number of breakpoints being selected by the AIC or BIC (recommended). #code (example and code from Martin Maechler previous email) library(segmented) o<-selgmented(y, ~x, Kmax=20,

>>>>> Anupam Tyagi >>>>> on Tue, 9 Jul 2024 16:16:43 +0530 writes: > How can I do automatic knot selection while fitting piecewise linear > splines to two variables x and y? Which package to use to do it simply? I > also want to visualize the splines (and the scatter plot) with a graph. > Anupam NB: linear splines, i.e. piecewise

Dear List, I would greatly appreciate help on the following matter: The RuleFit program of Professor Friedman uses partial dependence plots to explore the effect of an explanatory variable on the response variable, after accounting for the average effects of the other variables. The plot method [plot(summary(rq(y ~ x1 + x2, t=seq(.1,.9,.05))))] of Professor Koenker's quantreg program

Hello, I would like to submit two papers that use LLVM to the Related Publications section. Both papers focus on code isolation applied to perform piecewise compiler optimizations. The code isolation process is performed by CERE, an open source tool based on LLVM. The second paper is an extended version of the first one. 1) Piecewise Holistic Autotuning of Compiler and Runtime Parameters

Dear Mihail, I've added these two publications to the publications page. Please review it and let me know if I need to make any changes. In particular, if you have URLs to use for the papers, having those would be greatly appreciated. Regards, John Criswell On 11/28/17 12:05 PM, Mihail Popov via llvm-dev wrote: > > Hello, > > I would like to submit two papers that use LLVM

To whom it may concern, 1. I would like to know if there is a command in R to choose a function for a given dataset. I am facing a difficult question about how to fit the data [ please attachment ] 2. Are there any function that will allow users to do the piecewise regression? If not, is it going to be provide in the new updated version? What I am using is the piecewise logistic regression,

Dear all, I'm attempting to use a piecewise regression to model the trajectory of reproductive traits with age in a longitudinal data set using a mixed model framework. The aim is to find three slopes and two points- the slope from low performance in early age to a point of high performance in middle age, the slope (may be 0) of the plateau from the start of high performance to the

I am a novice R user. I would like to be able to graph some simple piecewise functions/functions with domain restrictions in R, but I'm having trouble defining such functions. For example, I would like to define the following function: f(x)={x^2 if -1<x<x; 1 if 2<x<3} Notably, the function is undefined outside of domain (-1,1)U(2,3). My best attempt in R is something like

Hi, I am a biologist (relatively new to R) analyzing data which we predict to fit a power function. I was wondering if anyone knew a way to model piecewise functions in R, where across a range of values (0-x) the data is modeled as a power function, and across another range (x-inf) it is a linear function. This would be predicted by one of our hypotheses, and we would like to find the AICs

Dear all, I am just wondering if anybody has implemented a function that can give a piecewise linear interpolation in more than 2 dimensions? I have looked at the akima package, but I would rather like a piecewise linear interpolation rather than a spline and while it did the job quite satisfactory for 2 dimensions, I need to interpolate in at least three dimensions. If anybody has implemented

Which function implements the piecewise cubic Hermite interpolation? I am looking for equivalent of matlab's interp1 with the method = 'pchip' Here is the reference http://www.mathworks.com/access/helpdesk/help/techdoc/index.html?/access/helpdesk/help/techdoc/ref/interp1.html& -- View this message in context:

Hi All, I am trying to fit a piecewise lasso regression, but package Segmented does not work with Lars objects. Does any know of any package or implementation of piecewise lasso regression? Thanks, Lucas

Dear Forum, I have been wracking my head over this problem for the past few days. I have a dataset of (x,y). I have been able to obtain a nonlinear regression line using nls. However, we would like to do some statistical analysis. I would like to obtain a confidence interval for the curve. We thought we could divide up the curve into piecewise linear regressions and compute CIs from those